Luoyang, China
Luoyang, China

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Jin G.-H.,China Institute of Technology | Gao X.-Z.,China Institute of Technology | Li X.,China Institute of Technology | Chen Y.-G.,Unit 63880
Yuhang Xuebao/Journal of Astronautics | Year: 2010

The high velocity motion compensation is the key technique for restoring the profile resolution and improving the clarity of ISAR image. The paper proposed a new compensation method based on chirplet transform. The dominant scattering center echo is reconstructed based on windowed rough ISAR image. And the effect of multi-scattering centers on chirp rate is avoided. By chirplet decomposition, the chirp rate is obtained, the velocity is estimated and the phase error is compensated. The experimental result shows that the algorithm is effective.

Jin G.-H.,China Institute of Technology | Gao X.-Z.,China Institute of Technology | Li X.,China Institute of Technology | Chen Y.-G.,Unit 63880
Xitong Fangzhen Xuebao / Journal of System Simulation | Year: 2010

The micro-precession dynamics model was improved. And the micro-precession mathematic formulas were set up. The mid-course targets' traits were analyzed from the aspects of target shape, motion specialty and scattering specialty. And the moving scattering center model was raised. In the end, the simulation results provide important foundations to mid-course target recognition.

Chen J.,Beihang University | Liu Y.,Unit 63880 | Niu H.-B.,Unit 63916
2012 10th International Symposium on Antennas, Propagation and EM Theory, ISAPE 2012 | Year: 2012

We proposes an interference mathematical model of LMS algorithm beam forming after analyzing LMS using matrix theory, and we also build another mathematical model of output SINR (Signal to Interference and Noise Ratio) by assuming the signal and interference are unrelated. Then, based on these models, we further analyze the anti-noise performance of LMS algorithm when there are no inference signals, while when there are interference signals we make the conclusion that the algorithm affects the interference totally different under different degree of interference. At last, we test and verify our analysis using mathematical emulation, and make the performance appraisal of anti-interference technology with adaptive nulling antenna. © 2012 IEEE.

Jin G.-H.,Hunan Institute of Technology | Gao X.-Z.,Hunan Institute of Technology | Li X.,Hunan Institute of Technology | Chen Y.-G.,Unit 63880
Tien Tzu Hsueh Pao/Acta Electronica Sinica | Year: 2010

The precession parameters of ballistic targets are of great importance to warheads and decoys discrimination. Based on dynamic ISAR image sequence, this paper analyzes the specialties of scattering and ISAR imaging of spatial ballistic targets. The history of posture changing is deduced. And a method for posture difference evaluating based on image registration is proposed. Moreover, equal interval registration method is adopted to avoid singular registration. Precession parameters are extracted based on posture difference curve. And the extraction process is presented detailedly. Experimental results show that the posture difference can be estimated correctly and the precession parameter estimation has good precision.

Zhao C.,Capital Normal University | Shi C.,Capital Normal University | Zhao Y.,Yunnan Technician College | Liu Y.,Unit 63880
Applied Mechanics and Materials | Year: 2011

To overcome the shortcomings of the traditional passive-radar-seeker(PRS) for anti-decoy, a complex angle measuring method is proposed in this letter. The complex angle measuring method consists of monopulse angle and spatial spectrum estimation, two angle-measuring units. PRS can get the angle high-resolution features through the complex angle measuring method. So it is possible that PRS confronts decoy. Finally, the simulation results verify the feasibility and anti-decoy capacity of the complex angle-measuring method.© (2011) Trans Tech Publications.

Rao B.,National University of Defense Technology | Zhao Y.-L.,Unit 63880 | Xiao S.-P.,National University of Defense Technology | Wang X.-S.,National University of Defense Technology
IET Radar, Sonar and Navigation | Year: 2010

Range deception is a common electronic countermeasure technique used for ballistic missile penetration. The well-designed decoys of range deception can even form stable tracks. Discrimination of these decoys is difficult and one potential way is at radar data processing level by using motion features. This study presents a novel method, called acceleration matched discrimination algorithm, which fully utilises the fact that the accelerations of exo-atmospheric active decoys are essentially different from that of physical targets (e.g. warhead), that can discriminate these decoys at the radar data processing level. First, the acceleration model of active decoys is explicitly derived. Secondly, the acceleration matched coefficient (AMC) is defined based on the filtered acceleration and theoretical acceleration. By employing the extended Kalman filter, the instantaneous variance of AMC is also derived. Finally, the discrimination algorithm is designed based on a batch-processing weighted least squares estimate and its estimated variance. Theoretical analysis and simulations indicate that the discrimination method is valid and feasible. Furthermore, the discrimination performance analysis due to the influence of radar position, radar measurement error and data rate are also covered. © 2010 The Institution of Engineering and Technology.

Liu Z.-M.,National University of Defense Technology | Lu Z.-Y.,Unit 63880 | Huang Z.-T.,National University of Defense Technology | Zhou Y.-Y.,National University of Defense Technology
IET Radar, Sonar and Navigation | Year: 2011

In this study, a characteristic equation-based Gerschgorin disk estimator (CE-GDE) is proposed for source enumeration. In CE-GDE, the diagonal averages of the array output covariance matrix of a uniform linear array are used to form a new data matrix, whose rank equals the number of the incident signals. Then the signal number is estimated by detecting the rank of this matrix with the Gerschgorin disk estimator. Numerical examples show that CE-GDE surpasses existing methods in scenarios of both spatially uniform and non-uniform noise. © The Institution of Engineering and Technology 2011.

Liu Y.-Q.,Zhengzhou University | Liu C.-C.,Zhengzhou University | Zhao Y.-J.,Zhengzhou University | Zhu J.-D.,Unit 63880
Wuli Xuebao/Acta Physica Sinica | Year: 2015

The existing blind beamforming methods are effective only under the condition that the source signals have some special statistical or structural characteristics. Additionally, the structure of cascade model is complicated and the stability of parallel model is poor when dealing with multi-target signals. To address these problems, a novel blind beamforming algorithm for multi-target signals based on time-frequency (TF) analysis is proposed in this paper. The received array signals are first transformed into time-frequency domain by using quadratic time-frequency distributions (TFDs). Then, the single-source auto-term TF points which show energy concentration at a single signal are extracted through three operations: (i) removing noise points by setting a reasonable threshold, (ii) separating auto-term TF points from cross-term points, and (iii) selecting the single-source auto-term TF points from the auto-term ones. Moreover, these single-source auto-term TF points are classified by the principal eigenvector of their spatial time-frequency distribution matrixes. For each class of TF points, the uncertain set of signal steering vector is given, whose radius is defined as the ultimate range between the center and the elements in the class. Within the uncertain set, an optimization algorithm is provided to get the optimal estimation of the signal steering vector. Finally, the blind beamforming for multi-target signals is achieved based on the Capon method, which can enhance the desired signals and suppress the noise and interference signals. In addition, the influence of parameters selection, the clustering method of unknown source number, and the computational complexity of the proposed algorithm are analyzed. The proposed algorithm can achieve parallel output of multi-target signals under the condition that the array manifold and the direction of arrival (DOA) are unknown. Also, the complex iterative solving processing may be avoided and special limitations on signal characteristics are unnecessary. As a result, it has wide applicability and superior stability compared with the existing blind beamforming methods. Simulations illustrate that the proposed algorithm can well separate multi-target signals which are TF-nondisjoint to a certain extent. It can achieve a higher output signal to interference plus noise ratio (SINR) compared with the constant modulus algorithm (CMA), the independent component analysis (ICA) algorithm, and the joint approximate diagolization of eigenmald (JADE) algorithm. Furthermore, the output performance of the proposed algorithm is close to the optimal Capon beamformer. ©, 2015, Chinese Physical Society. All right reserved.

Xu J.,Zhengzhou University | Wu F.,Zhengzhou University | Qian H.,Zhengzhou University | Ma F.,Unit 63880
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | Year: 2013

Settlement matching is one of the kernel parts of multi-source spatial data fusion and multi-scale data updating. Following the cognition habits of mankind in finding strange buildings, the spatial relationship similarity is used to assist the settlement matching process. The discrete computing method according with human cognitive habits is proposed after analyzed the similarity of topological relationship, distance relationship and direction relationship. And the matching processes are as fellows. Firstly, the outstanding settlement of the original object is picked up and computed to find its matching object. Secondly, referencing the matched object, the next matching object is achieved by the extend-first traversal to unmatched objects. Thirdly, the precision matching is fulfilled by traversing every settlement object all in this way. Finally, the matching quality is evaluated by comparing the spatial relationship similarity of adjacent objects. Test illustrates that this method can effectively improve the matching precision in the case of data hardly displacement and high settlement shape homogeneity.

Kang J.,Ordnance Engineering College | Tang L.,Ordnance Engineering College | Zuo X.,Ordnance Engineering College | Li A.,Ordnance Engineering College | Li H.,Unit 63880
Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010 | Year: 2010

Aiming at the monitored nonstationary signal in sensor networks, distributed compressed sensing-based data aggregation model and algorithm, DCS-DF-1, is presented to reduce the number of transmissions in sensor networks and improve the precision of sensing. To implement this algorithm, the variance of each recover sensing sequence of sensor is estimated using the wavelet transform, and the optimum weighting factor to each sensing is obtained accordingly. The fusion performance is better than each sensor and MMSE-based (minimum mean square error) method. Besides, analyze the influences of number of non-zero components to CPU time, SNR (signal-to-noise ratio), MSE (mean square error) and recover error of algorithm, as well as the relation of energy consumption to recover error. The calculation results show that DCS-DF-1 not only have better performance of stability and consistency, but also satisfy the monitoring requirements for non-stationary signal in sensor networks. © 2010 IEEE.

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